The current issue of the IETE Journal of Research (Volume 69 Number 12, December 2023) contains seventy articles. The subsequent articles encompass recent breakthroughs and ongoing investigations in various fields, including communications (1), electromagnetics (8), opto-electronics (1), computers and computing (26), control engineering (8), electronic circuits, devices and components (9), instrumentation and measurement (5), medical electronics (4), and power electronics (8).
The number of article on Communications in this issue is one, in order of the subject areas listed above. Average bit error rate is examined in the paper “Error Rate Analysis of Different Modulation Schemes over Shadowed Beaulieu-Xie Fading Channels”. Various coherent and non-coherent modulation methods are examined. ABER equations are derived from shaded BX fading channel output signal to noise ratio probability density function. A unique closed-form ABER formula for Gray-coded rectangular quadrature amplitude modulation over shadowed BX channel is also studied. Researchers compare how fading and shadowing effect modulation.
Eight articles in the general area of electromagnetics are included in this issue. In the paper,” Development of Multi Cavity-Backed Stacked Multi-Resonator Microstrip Antenna, authors examine a two-layer, four-top, bottom-stacked, rectangular microstrip antenna with up to four cavities for multi-cavity backfilling. The study demonstrates that antennas with three cavities increase isolation, gain, and bandwidth. Single and triple cavity-backed rectangular microstrip antennas beat non-cavity stacked ones in bandwidth (83% vs. 40%) and gain (0.80 dB vs 2.20 dB). The recommended antenna is suitable for Through the Wall and Ground Penetrating Radar due to its improved S-band characteristics. A parallel coupled line-based compact dual-band bandpass filter is proposed in “A Compact Dual-Band Bandpass Filter using Coupled Microstrip Lines”. The design incorporates transmission zeros (TZs) in a single-wideband filter's frequency response. The proposed broad bandpass filter has three connected lines and a multi-mode resonator. A new notch filter is made from two coupled lines joined at the end and loaded by an open-circuit stub. Rogers RO3210 substrate is used to build DB-BPF for WLAN applications. In the paper “A Compact MIMO Antenna for 5G NR frequency bands n257/n258/n261 under Millimeter-Wave Communication,” a compact, planar, 4-port UWB MIMO antenna is proposed for fifth-generation millimeter-wave applications. MIMO antenna design with four identical hexagonal-shaped slotted ground planes and four microstrip line feeds is proposed. Impedance bandwidth of 30.47% over 26.7 GHz to 36.3 GHz makes the proposed MIMO antenna appropriate for 5G New Radiofrequency bands. Simulated and experimental results correlate positively. The author of the paper “Antenna Array Performance Diagnostics Using Theory of Collapsed Distributions” suggests a way to use the theory of collapsed distributions (TCD) to greatly cut down on the time needed to do calculations and show a few designs for wide scan antenna arrays. The concept of mean or average inter-element spacing, which is determined with TCD, is used to predict the effect of mutual coupling and the onset of grating lobes. Using TCD, the author developed and showed that a sparse antenna array has better scan performance than normal or dense antenna arrays. The manuscript titled “Compact Multi-slotted Printed Antenna for Ultra Wideband Applications in Medical Telemetry” introduces two distinct designs of compact microstrip patch antennas that possess features specific to the ultra-wideband range. The antenna designs that have been demonstrated are intended for use in medical telemetry. In order to increase the bandwidth of the slotted rectangular patch antenna equipped with notches over the ultra-wideband, geometrical optimizations are performed. In contrast to the prevailing approach, the microstrip patch antenna is optimized by taking into account an infinite substrate. The impact of a finite substrate on the microstrip patch's bandwidth is examined, yielding improved outcomes in terms of compactness, simplicity, and bandwidth. The authors of the paper “Triple Band-stop Performance Realization Through a Single Substrate Layer Frequency Selective Surface” create a single-substrate-layer Frequency Selective Surface (FSS) with a 1.6 mm thick FR4 substrate for Bluetooth, WLAN, WiMAX, and X-band frequency filtering applications. On the front, the suggested FSS unit cell has two polygon loops. On the back, it has a square loop with four annular rings connected to its corners. The system being sold works at three different frequency ranges: 2.3–4 GHz, 5–6 GHz, and 8–12 GHz. At 3.3 GHz, 5.6 GHz, and 9.9 GHz, there are three resonances. Formulas for the LC parameters are provided along with a corresponding circuit model of the suggested structure. The authors of the paper “Wide Bandwidth Axial Ratio Circularly Polarized Array Antenna based on External Resonator” use a dual-layer and microstrip patch array antenna together to create waves that are linearly polarized. Straight-line polarized (LP) waves are changed into circularly polarized (CP) waves on the outside by a four-layer dual rings polarizer. At 5GHz, the bandwidth of a small circular polarized array antenna is 20% and the bandwidth of a large circular polarized array antenna is 27.06%. Tests and models showed that the axial ratio bandwidth (ARBW) at 5 GHz is 17% at 3dB. The antenna is easy to put together, has a wide ARBW, and is low in resistance. These factors make the suggested antenna a great choice for satellite contact. The article “Zig-Zagmonofilar Spiral Shaped CRLH TL based Compact Lowpass mono-/duo-/tri-/quad-bandpass Filter” describes how to create a planar CRLH TL-based compact lowpass filter. Filters are formed from two unit-cells of ZZMSL and ZZOR on the main transmission line. Only the ZZMSL length that fits inside ZZOR's configured length makes up the various passbands. This implies that all filters are of the same size. This innovative low-pass quad-band-pass filter features a smaller size, reduced in-band insertion loss, good band-to-band separation, an adjustable center frequency with good out-of-band skirts, and less circuit complexity. Matching electromagnetic simulation, circuit model simulation, and measurement data verify the design process and filter efficacy.
This issue comprises one opto-electronics related research article. The paper, entitled “Realization of Optical DEMUX using Machine Learning Model: A Future Paradigm for Optical VLSI System” talks about how to use machine learning with ANN to build 101 channels of optical DEMUX in the 1300 nm to 1400 nm range. The goal of this work is to imagine the optical parameters of a silicon grating structure, including the width of SiO and Si. These parameters are what determine whether the desired signal can pass through the structure and achieve optical DEMUX.
There are twenty six papers in this issue that covers different parts of computers and computing. The paper “A Quasi-Oppositional Based Flamingo Search Algorithm Integrated with Generalized Ring Crossover For Effective Feature Selection” proposes a hybrid feature selection approach. The recommended technique uses a novel hybrid Quasi oppositional-based Flamingo search algorithm with Generalized Ring Crossover (QOFSA-GRC) model to locate the dataset's most essential characteristics. This Quasi oppositional based Flamingo search algorithm (QOFSA) builds two groups: one using learning and the other using the algorithm. to cure the curse of dimensionality. The UCI repository dataset is then used to choose various relevant characteristics using generalized ring crossing. Finally, the Kernel Extreme Learning Machine (KELM) predictor verifies the features. In “ADS-Classif: A Robust Tool for Classifying Documents from Diverse Sources using Weighted Domain-Specific Vocabulary”, authors offer a supervised generic algorithmic approach to construct a domain-specific vocabulary. From labeled real-time domain corpus, the model estimates domain-indicative word combinations' weights and inclusion time to explain their semantic behavior in the current development age. ADS-Classif classifies real-time documents from various sources and tests domain-specific vocabulary's importance. The authors of the article titled “An Efficient Encoder-Decoder CNN for Brain Tumor Segmentation in MRI Images” present an enhanced architecture of an encoder-decoder convolutional neural network (CNN) designed specifically for the purpose of segmenting brain tumors in magnetic resonance imaging (MRI) data. Three encoding and decoding parts make up its structure. Each input slice is individually convolved with two distinct filters in the initial encoding block. Subsequently, the processed slices are passed through subsequent encoding and decoding blocks in order to extract the hierarchy of tumoral features. The paper “AR Computer-Assisted Learning for Children with ASD based on Hand Gesture and Voice Interaction.” presents a speech-and-gestural-based learning framework that delivers visual help, engagement, and interaction. This approach can aid ASD kids in school and cognitive treatment. This prototype was designed to make kids more active and attentive during the session so they felt more included and social. Structured activities and augmented reality games are produced for area autism spectrum disorder therapy providers. In “Atrous Fully Convolved Depth concatenated neural network with Enriched Encoder for Retinal artery-vein classification”, authors propose a deep semantic segmentation-based Atrous EEDCFCNN architecture for artery vein classification. Public databases DRIVE, INSPIRE, and IOSTAR perform better with the suggested design. The authors of the paper “Big Data Classification Using Enhanced Dynamic KPCA and Convolutional Multi-Layer Bi-LSTM Network” present a methodology consisting of data preprocessing, feature extraction, and classification for assessing the effectiveness of Big Data. In “Clinical Assessment of Diabetic Foot Ulcers Using GWO-CNN based Hyperspectral Image Processing Approach”, authors suggest a new image processing approach for DFU picture assessment and categorization. After cascaded fuzzy filter pre-processing, nonlinear partial differential equation (NPDE)-based segmentation segments foot ulcer regions. Local binary pattern (LBP) is used to extract valuable characteristics. These features are used by the hybrid Grey Wolf Optimization-Convolutional Neural Network (GWO-CNN) model to identify DFU zones. Estimating performance measures and comparing the results to current algorithms shows the efficacy of the suggested technique. The authors of the paper “Clinical Decision Support System for Ophthalmologists for Eye Disease Classification” compare and contrast the performance metrics and development of an eye disease classifier that effectively detects and categorizes DME, DRUSEN, and CNV with those of a feature extractor constructed using various deep-learning pre-trained CNN models. The objective of the clinical decision support system is to aid ophthalmologists in the classification of these three distinct types of eye diseases. In “Cloud Computing and Machine Learning based Electrical Fault Detection in PV System”, authors build pre-trained machine learning model applications. An appropriate algorithm is designed and put on a web server after training the dataset for various electrical difficulties in a solar array for accurate categorization. Data for the algorithm is collected by simulating the PV system in MATLAB/Simulink under various operating conditions. testing accuracy for randomly divided data. The authors of the paper “Cross-Task Cognitive Load Classification with Identity Mapping-based Distributed CNN and Attention-based RNN using Gabor Decomposed Data Images” talk about creating a strong classification model called CARNN. It uses a deep structure of connected branches of convolutional neural networks with leftover blocks through identity mappings and recurrent neural networks with attention mechanisms to help each person do better at their work. Psychosocial factors affect how well people take on different tasks, which makes it hard to create a reliable model for using the electroencephalogram to classify cross-task cognitive stress. In “Deep Active Contour based Capsule Network for Medical Image Segmentation (MIS),” authors discuss the network's architecture and loss function, two key performance criteria in Deep Learning for medical image segmentation. Both are studied to boost MIS dice-score. They use an active contours model to include regional information, external influences, and functional choices into their loss function. They compared Dice-score and mean-IoU brain Tumor segmentation dataset performance and found promising results. In “Design of Internet of Things (IoT) System Based Smart City Model on Raspberry Pi”, authors look at the strategy and execution of an IoT-based smart city. This study uses Raspberry Pi to construct an urban IoT system to help smart cities handle home issues. Comparison to Raspberry Pi-based smart city development strategies shows a better approach. In “Enhancing Software Reliability and Fault Detection using Hybrid Brainstorm Optimization based LSTM Model”, authors propose a stepwise prediction model for software fault detection and correction using a hybrid long short-term memory (LSTM) with Brainstorm Optimization and Late Acceptance Hill Climbing (BSO-LAHC) algorithm The proposed method is cheaper and faster. Using Firefox and Bugzilla datasets, the proposed hybrid with the BSO-LAHC algorithm outperformed existing techniques. In “GIL-CNN: A Novel Multipath Features for COVID-19 Detection Using CT-Scan Images”, authors classify healthy and COVID patients using CT scans. The suggested model avoids spatial loss by providing global, intermediate, and local features for CT scan image feature representation. It can help identify COVID-19 patients automatically, relieving healthcare systems. In “H-Map based Technique for Mining High Average Utility Itemset”, authors propose Upper Bound using Remaining Items Utility, Maximum Itemset Utility, and Sum of Maximum Utility in a Transaction. It also uses multithreaded parallel processing to speed up processing. The H-Map data structure used to store utility values reduces search time and joins for itemset expansion compared to current High Average Utility Itemset mining algorithms. Effective pruning algorithms for pruning weak candidate itemsets and an efficient data structure for storing utility values improve system efficiency. The authors of the paper “Human Muscle Synergy Recruitment and Variability Assessment for Walking Speed Prediction Module Design” looked into how the neural system tells muscles to work together to make people walk at different speeds and came up with an algorithm for predicting walking speed. Findings from the study will help with controlling lower leg assistive or rehabilitation devices and making a good human-machine interface. Authors of the paper “Improved Unsupervised Statistical Machine Translation via Unsupervised Word Sense Disambiguation for a Low-resource and Indic languages” try to solve the issue of poor translation quality caused by words that aren't aligned or sensed correctly. They do this by adding unsupervised Word Sense Disambiguation (WSD) to the decoding phase of USMT. Authors study IoT security enhancement for IDS creation using ensemble learning and classifier performance methodologies in “Intrusion Detection System with an Ensemble Learning and Feature Selection Framework for IoT Networks”. Preprocessing initiates the data cleansing, encoding, and normalization processes for the RPL-NIDDS17 dataset. The dataset is balanced using SMOTE. CNN also extracted dataset features. The Arithmetic Optimization Algorithm chooses optimal extracted characteristics. AOA with BOA uses classifier predictions to select the most-voted class. In “Keyphrase Extraction using Enhanced Word and Document Embedding”, authors suggest unsupervised keyword extraction. The proposed method used cutting-edge word and text embeddings to retrofit n-grams. It also presented a new way to assemble document vectors using essential word vectors and idf-scores. The study “Malayalam Question Answering System using Deep Learning Approaches” suggests a Malayalam QA system that uses deep learning techniques like Long Short-Term Memory Networks (LSTM), Gated Recurrent Units (GRU), and Memory Network models. Research on the Malayalam QA data can be made better with the scalable deep learning system. In the paper, “MilliNet: Applied Deep Learning Technique for Millimeter-Wave Based Object Detection and Classification”, authors introduce how millimeter-wave imaging can be used for surveillance and navigation. Radar takes pictures of millimeter waves, which are then sent to a brand-new neural network design called MilliNet. MilliNet is trained on LiDAR data (in the form of point clouds) and can be used to sort and divide millimeter-wave image input using features like permutation and symmetric invariance. This gives a three-dimensional picture even when the weather is bad, and it's easy to use that information to find objects and put them into groups. The model's results from a dataset is checked and proven to work in a variety of situations and with various types of items. In the paper “Multimodal Emotion Recognition Framework using Decision Level Fusion and Feature Level Fusion Approach” offers leveraging decision- and feature-level data to detect feelings. The first method recommends decision level fusion. This late fusion uses modality-specific models. First, IEMOCAP Database data is tokenized at 128 characters. Then it goes to a transformer-based BERT model. Feature Level Fusion is the second way. Combining features from each modality and delivering them to the attention-based LSTM is early fusion. The IEMOCAP Database contains text, audio, and video. Text, audio, and video are removed using the CNN model, OPENSMILE toolkit, and 3D-CNN design. Python duplicates the methods shown. Performance measurements include recall, precision, accuracy, and sensitivity. Then, the expected first technique is compared to the second to see which performs better. Simulations show the second method works better. In “Partially Visible Lane Detection with Hierarchical Supervision Approach”, authors present a deep supervision-based model to detect partially visible lane lines. The model tracks and classifies lane features at different scales using hierarchical (Deep) supervision. Compared to a known model, the suggested model simulates incomplete lane paint visibility with robust results. In “Smart Technique of Insulin Dose Prediction for Type-1 Diabetic Patients”, researchers offer a control system to keep type-1 diabetics' blood glucose levels normal. The suggested protocol uses a WBAN and controller. WBAN monitors blood glucose and insulin levels regularly. The controller predicts maximum glucose from meal quantity. Using patient-specific insulin sensitivity, the projected glucose level predicts the insulin dose. “Synthesis of Concentric Circular Antenna Array Using Whale Optimization Algorithm (WOA)” optimizes concentric circular antenna array performance utilizing benchmark functions and radiation patterns. A number of benchmark methods present simulation results. WOA algorithm capability is further examined by pattern synthesis for thinned and non-uniformly stimulated arrays for four CCAA geometries. Optimization results illustrate WOA's optimization expertise. The Paper “W-Net: Novel Deep Supervision for Deep Learning-Based Cardiac Magnetic Resonance Imaging Segmentation” proposes employing U-Net-based architecture and unique deep supervision to improve segmentation. A closely observed W-Net creates a second path that runs alongside the decoder path in a U-Net-based system. Each upsampling layer's output is mixed with pixel-wise addition in the decoder pipeline to reuse features. Loss is calculated per feature dimension on the deep supervision layer. This enhances training for all layers by implanting gradients deeper into the network. The proposed W-Net could improve CMRI segmentation, heart assessment, and disease diagnosis.
Eight articles in this issue deal with control engineering. In the paper “AGC in the Multi-Area Thermal System with Integration of Distribution Generation on the Frequency of the System Using the Classical PID & Hybrid Neuro-Fuzzy Controllers” proposes a new hybrid neuro-fuzzy system for the AGC model of two power systems that cover the same area. Installing non-traditional energy sources allows electricity buyers and sellers make economic decisions. Proposed model involves distribution generation. First, the two-equal-area AGC uses a normal PID controller with DG. Second, ANFIS with distributed generation is used to examine the Automatic Generation Control (AGC) plan for two equal areas. Simulations reveal that an ANFIS with a DG-based PID controller performs better and more reliably than the PID investigated without and with the DG-based approach. The authors of the paper “Controlling and Monitoring of a Solar-Powered DC Motor using a Wireless Sensor Network” suggest a PV system that includes a solar panel, a buck-boost converter, a separately excited (S.E.) DC motor, and controllers like Proportional Integral Derivative (PID), Fuzzy, fuzzy based on PID (FPID), and Artificial Neural Network (ANN). The purpose of this system is to handle non-linearity and uncertainty in the system. A Data Dashboard for LabVIEW and a wireless sensor network are used to keep an eye on and manage the system. The next paper, “Coordinated Control of ALFC-AVR in Multiarea Multisource Systems Integrated with VRFB and TCPS using CFPDN-PIDN Controller”, talks about how the vanadium redox flow battery (VRFB) and thyristor control phase shifter (TCPS) work together to change the automatic load frequency control (ALFC) and automatic voltage regulator (AVR) of three area hydrothermal systems that use renewable energy sources. Along with thermal and hydropower, Area-I, Area-II, and Area-III each have a solar thermal power plant, a dish-stirling solar thermal system, and a geothermal power plant. For both thermal and hydro plants, an appropriate generation rate constraint and governor dead band are taken into account. The paper “Coordinated Wide-Area Damping Control in Modern Power Systems Embedded with Utility-Scale Wind-Solar Plants” discusses how to control power system stabilizers (PSSs), static synchronous compensators (STATCOM), and static synchronous series compensators (SSSC) for grid-forming resources that use wind and solar PV. This work aims to increase inter-area oscillation damping while maintaining voltage and frequency within the permissible range and considering practical uncertainties. StatCOM improves voltage and reactive power, and an SSSC with the coordinated wide-area damping controller (CWADC) adds dampers. To prove the CWADC works, nonlinear time-domain simulations are done on a modified IEEE 68-bus test system with hybrid wind-solar power plants that account for different time delays.In the next paper “Impact of RFB and PLL Dynamic on Combined ALFC-AVR Regulation of Multiarea Multisource System under Deregulated Environment with AC/accurate HVDC link” talks about how the redox flow battery (RFB) and accurate high voltage dc (AHVDC) link work together to control the voltage and frequency of two-area systems in a deregulated environment. It has been tried for the first time to use a cascaded fractional-order PD with filter coefficient and a PID with filter coefficient as a secondary controller. It turns out that the suggested CFOPDN-PIDN controller works better than the PIDN controller in all three power transactions in a deregulated setting. The study shows that the system damping was better when RFB and AHVDC links were used together with PLL dynamics than when RFB and AC links were used alone. The paper “Kalman Filter based DC Bus Voltage Control for Autonomous DC Microgrid System with PV, Wind, and EVs Integration” examines a battery unit voltage-current control algorithm that uses a Kalman Filter to accurately control the medium voltage direct current (MVDC) bus voltage with only minor oscillations compared to the traditional VI algorithm. In this study, an EV control approach is presented. The purpose is to make EV charging easier if the system's power exceeds its load. This is done with current loop management. In “Performance Assessment of Novel Solar Thermal based Dual Hybrid Microgrid System using CBOA Optimised Cascaded PI-TID Controller”, authors evaluate the frequency control of a dual-area hybrid microgrid (DHM) with solar thermal systems, biodiesel generators, energy storage, and DC link. Cascaded PI-TID controller adjusted gain limits are achieved using chaotic butterfly optimization (CBOA). Integrating a solar gas turbine and solar chimney for load frequency control research is innovative. Using CBOA to tune cascaded PI-TID controllers is also novel. The authors of the paper “Simple Synchronization Scheme for a Class of Nonlinear Chaotic Systems using a Single Input Control” talk about a general way to deal with the problems of synchronization in a drive-response setup for a group of nonlinear chaotic and hyperchaotic systems. This paper uses Lyapunov's stability theory and a single input control to bring two chaotic or hyperchaotic systems in a drive-response configuration into sync. This single input feedback controller shows that the response system's state variables are in sync with the drive system's matching state variables.
Nine articles in this issue cover the expansive topic of electronic circuits devices and components. The researchers who wrote the paper “1 V, 20 nW true RMS to DC Converter based on Third Order Dynamic Translinear Loop” describe a new type of current-mode true RMS-DC converter that works with the dynamic trans linear principle. A third-order translinear loop was used to build the converter, which makes for a very small and straightforward circuit. They designed the suggested circuit using 65 nm CMOS technology. It works well with an input current range of 300 nA to 950 nA and a frequency range of 600 Hz to 650 kHz for a capacitance value of 10 nF. The suggested converter is put into a standard ECG detection system to see how well it works in the real world. The results show that the circuit is a good choice for RMS-DC conversion in low-voltage, low-power situations. The paper “Bovine Serum Albumin Based Thin-Film Capacitors for Flexible Electronic Applications” describes how the authors made the capacitors. They used the spin coating technique to put layers of bovine serum albumin (BSA) on indium tin oxide (ITO) coated polyethylene terephthalate (PET) substrates that are electrically conductive and optically clear. The metal contacts on top of the BSA films were made by thermal evaporation of gaseous phase aluminium. They test the mechanical flexibility and curvature of the materials to see if BSA-based MIM thin-film capacitors could be used in flexible electronic applications soon. In the paper “Demonstration of Temperature Dependent Analysis of GAA – β-(AlGa) 2O3 /Ga2O3 High Electron Mobility Transistor” authors describe how the Gate all around (GAA)-β-AGO/GO HEMT was designed and shown to achieve high current density, electron mobility, and electron velocity at cryogenic temperatures. Better control of the gate is possible in a structure based on GAA. This makes the suggested device work better across a wider temperature range. For power switching tasks, this kind of device is used. “Design and Analysis of CMOS Dynamic Comparator for High-Speed Low Power Applications using Charge Sharing Technique” is a paper that describes a new dynamic comparator and looks at its design in terms of delay and power. The expression is found for all of the transistor's operational areas. The new design is suggested because it requires less power and make the system faster. Existing comparator designs have problems like limited frequency range, high lag, and more power loss. The new design fixes these issues. In the paper “Design of Proficient Two Operand Adder Using Hybrid Carry Select Adder with FPGA Implementation” is a paper that talks about a way to use a different VLSI hybrid carry select adder design. The suggested hybrid technology-based Carry Select adder (CSELA) has two stages: the Hancarlson adder stage (LSB) and the Hybrid Stage (MSB). This method does all the steps (4 bits in each stage) at the same time to make the speed and area even better. The suggested adder's propagation delays are made up of two full adders, seven multiplexers (4:1), and a three-bit BEC for making cout. The suggested work shows that the hybrid carry select adder works quickly and takes up less space than a regular adder. The researchers of the article “Diminish Short Channel Effects on Cylindrical GAA Hetero-gate Dielectric TFET using High Density Delta”, present a novel concept for a Gate All Around (GAA) hetero dielectric gate-cylindrical tunnel field effect transistor (TFET) with the intention of minimizing SCEs. The heterodielectric gate (HeG) described in this article is integrated with a Silicon-Germanium (Si-Ge) substrate. In order to attain an elevated ION value and a resilient IOFF value, accompanied by a steepest subthreshold swing (SS), an innovative high-density delta (HDD) layer is positioned in front of the source-channel junction. Systematic AC and DC parameter analysis shows that hetero-gate dielectric Cyl-TFET with high density delta (HDD) is better than conventional topologies. In the next paper “Investigation of Step Fin (SF), Step Drain (SD), and Step Source (SS) FinFETs with Trap Effect” is a paper in which the authors use 3D TCAD simulation to examine the RF and analog performance of the triple material gate (TMG) step Fin (SF), step drain (SD), and step source (SS) FinFET. The performance has been simulated under two distributions: Uniform trap (UT) and Gaussian trap (GT), where the concentration of the trap remains constant. The various DC parameters such as threshold voltage (Vth), sub-threshold swing (SS), and switching ratio are observed in the presence of trap distribution. The outcomes are encouraging. The authors of the article “Particle Swarm Optimization-based Band-pass Filter Using Switched-Fractional Capacitors” describe the construction of a fractional band-pass filter by substituting resistors with switched capacitors and switched fractional capacitors. Particle swarm optimization (PSO) is the method by which the optimal values are determined. Research has shown that filter parameters such as rise-time, settling-time, and peak-overshoot exhibit enhancements when compared to their integer-order counterparts. The next paper presents determination of “Two-port Equivalent Circuits deduced from S-parameter Measurements of NaCl Solutions”. Input impedances Zin and transmission coefficients S21 calculated from the deduced two-port equivalent circuits of the NaCl solutions were consistent with the measured S-parameters
Five articles in this issue deal with instrumentation and measurement. In “Artificial Intelligence and Multi-Sensor Fusion Based Universal Fire Detection System for Smart Buildings Using IoT Techniques,” writers develop a fire prevention system that integrates non-visual and visual fire detection. Through a deep learning model on the Raspberry Pi 3B+, the visual technique uses artificial intelligence. Transfer learning pertains to MobileNet deep learning. The second subsystem identifies fire causes and prevention measures. In “Back-up Protection Scheme for Series Compensated Transmission Line Connected to Wind farm,” authors describe an algorithm to protect series-compensated transmission lines (SCTLs) connected with wind farms. To distinguish internal and exterior faults, the method uses the phase difference between the positive sequence currents at the TL ends. The complicated power difference at the TL endpoints identifies the internal fault phase. This technique is tested for reliability and applicability using extensive simulations with many fault and system factors. In “Intelligent Welding Defect Detection Model on Improved R-CNN”, authors create an end-to-end automatic X-ray welding flaw detection model using deep learning method to improve accuracy and efficiency. The deep residual network Res2Net is used to improve Faster R-CNN. Experimental results demonstrate that this strategy can increase welding flaw detection accuracy and efficiency to improve the original backbone network's feature extraction capabilities. In “Investigation on Multi-entropy and Multi-statistical Features Fusion Approach for Fault Detection in Rolling Bearing Using VMD”, authors propose targeting outliers in bearing fault detection. The suggested method compares entropy and statistical features taken from modes functions following variational mode decomposition (VMD) of recorded signals. Experimental results demonstrated that entropy-based features outperformed statistical features in bearing detection. In the paper, “Room Response Equalization of Non-Minimum Phase Systems using Kautz Filter and Sparse Autoencoder: A Hybrid Approach”, authors present a novel technique by cascading a Kautz filter and a sparse auto-encoder in performing room equalization to provide a listener with a profound audio experience alike the original audio signal. Computational results show that this hybrid approach yields better results both qualitatively and quantitatively in comparison with the other filtering techniques.
Four articles in this issue cover the expansive topic of medical electronics. In “A Compact On/Off-Body Dual Band Antenna with Modified Ground for Healthcare Applications”, authors develop and build a compact dual-band radiator for on/off body communication. It resonates in ISM-I and WLAN bands. The proposed antenna is parametrically investigated and its electric field and SAR at different arm positions are analyzed to determine its medicinal uses. Its SAR meets IEEE standards, and the prototype's measurements confirm the simulation. As a solution to the problems with Tele-radiology, the authors of the article “Abnormality Detection in Kidney Ultrasound Images by various classifiers with FPGA” propose a method that makes use of computer-aided diagnosis. For this purpose, they have employed the Random Forest Classifier to identify renal anomalies. Both the simulation and the implementation were carried out using the Xilinx Spartan-6 FPGA board with Modelsim 6.4a. In “Distance Metric-based Segmentation and Score Level Classification for Optimized Tumor Identification in MR Images”, authors use a Modified Decision Based Coupled Windows Median Filter (MDBCWMF) to pre-process (or filter) MR images, then send their output to a unique Fuzzy C-Means algorithm for segmentation, MDM-FCM. This strategy reduces segmentation error. With experimental evaluation using TCIA datasets, MDM-FCM segmentation outperforms other state-of-the-art techniques with classification accuracies. In the paper “Modified CNN Architecture for Efficient Classification of Glioma Brain Tumour”, authors propose a new model of modified CNN architecture for the classification of Gliomas. The modified CNN achieved a classification accuracy of 94.65%, which is significantly higher than the accuracy of the pre-trained AlexNet Model.
This issue comprises eight power electronics –related research articles. The paper “17-Level Quasi Z-Source Cascaded MI Topology Interfaced PV System: A Hybrid Technique” presents a 17-level QZS-CMI with fewer semiconductor switches for high-power photovoltaic applications with lower total harmonic distortion and higher performance. QZSI interfaces load and PV DC supply. Improved QZS-CMI design modeling maximizes PV power production. The proposed system is run on MATLAB/Simulink and compared against existing methods for efficiency. In “Fifth Order Generalized Integrator for Double-Stage Single-Phase Grid-Interfaced Photovoltaic Supply System”, authors use a fifth-order generalized integrator as orthogonal signal generator to generate grid synchronization signals. Solar power is sent to the grid using a single-ended primary inductor converter and H-bridge voltage source converter. System and control effectiveness are tested in a lab prototype employing Launch Pad TMS320F28379D digital signal processor. In the next paper “FPGA-based Statechart Controller for MPPT of a Photovoltaic System” develops an FPGA-based Statechart Controller for MPPT control of the PV system. Results from software-in-the-loop simulation (SILS) of the Statechart Controller are given. Comparing Statechart Controller performance to standard MPPT controller shows that it is more effective in tracking speeds, determinism, and modularity. In the paper “Harmonics Minimization in PUC Type Solar Multilevel Converter with Multicarrier Switching Schemes” examines the power quality of a seven-level three-phase packed U-cell (PUC) converter with multicarrier switching schemes. A modified carrier-based modulation method for solar PV array fed PUC inverter is introduced. The major goal is to reduce seven-level output voltage harmonics. It also raises the converter voltage basic component. Compare the proposed technique to other modulation systems to see its advantages. In “Multi-objective Spotted Hyena Optimization (MOSHO)-based Control of Grid-Tied PV System,” authors propose optimizing the incremental conductance (InC)-based maximum power point tracking (MPPT) algorithm step-size and PI controller gains for DC bus voltage regulation. The improved DC bus generates an accurate loss component of current, improving voltage source converter (VSC) reference current generation and power quality. In the next paper, “Performance Comparison of Optimization Algorithm tuned PID controllers in Positive Output Re-Lift Luo Converter Operation for Electric Vehicle Applications,” a Particle Swarm Based optimization algorithm is proposed to optimize the PID controller. Developing a better PID controller to test the re-lift Luo converter's reliability is innovative. Optimizing the closed-loop system with high voltage gain, power density, and efficiency improves its performance. In “Sun Flower Optimization with Self-Tuned Fuzzy Logic MPPT Controller and Reactive Power Compensation for Grid Connected PV System”, authors analyze reactive power compensation methodology to maximize power to single-phase grid-PV systems. This work aims to design a Sunflower Optimization (SFO) coupled with Self-tuned Fuzzy Logic Controller (SFLC)-based Maximum Peak Point Tracking (MPPT) management mechanism to maximize solar PV system power. The suggested system generates a clean sinusoidal grid side current with an appropriate grid voltage phase-shift to optimize system performance. The paper “Water Cycle Algorithm Based Parametric Tuning of Non-Negative LMMN Control of Grid Tied Renewable Energy Systems” proposes a hydrological cycle-based optimization technique for optimal control and performance enhancement of a three-phase grid integrated hybrid wind/photovoltaic (PV) system's non-negative least mean mixed norm (NNLMMN) voltage source control (VSC). Water cycle algorithm (WCA) tunes VSC proportional-integral (PI) controller parameters to moderate DC link voltage changes during dynamic load and wind situations. VSC performance is improved by generating a specific current loss component.
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Notes on contributors
Shiban K Koul
Shiban K Koul is currently an emeritus professor at the Indian Institute of Technology, Delhi. He served as deputy director (Strategy and Planning) at IIT Delhi from 2012 to 2016 and mentor deputy director (Strategy & Planning, International Affairs) at IIT Jammu from 2018 to 2021. He also served as the chairman of Astra Microwave Products Limited, Hyderabad from 2009 to 2019 and Dr R P Shenoy Astra Microwave chair professor at IIT Delhi from 2014 to 2019. His research interests include RF MEMS, high frequency wireless communication, microwave engineering, microwave passive and active circuits, device modelling, millimetre and sub-millimetre wave IC design, body area networks, flexible and wearable electronics, medical applications of sub-terahertz waves and reconfigurable microwave circuits including miniaturized antennas. He successfully completed 38 major sponsored projects, 52 consultancy projects and 61 technology development projects. He has authored/co-authored 615 research papers, 23 state-of-the art books, 4 book chapters and 2 e-books. He holds 26 patents, 6 copyrights and one trademark. He has guided 30 PhD thesis and more than 100 master’s theses. He is a Life Fellow of IEEE and Fellow of INAE and IETE. He is the chief editor of IETE Journal of Research, associate editor of the International Journal of Microwave and Wireless Technologies, Cambridge University Press. He served as a Distinguished Microwave Lecturer of IEEE MTT-S for the period 2012–2014.
Recipient of numerous awards including IEEE MTT Society Distinguished Educator Award (2014); Teaching Excellence Award (2012) from IIT Delhi; Indian National Science Academy (INSA) Young Scientist Award (1986); Top Invention Award (1991) of the National Research Development Council for his contributions to the indigenous development of ferrite phase shifter technology; VASVIK Award (1994) for the development of Ka- band components and phase shifters; Ram LalWadhwa Gold Medal (1995) from the Institution of Electronics and Telecommunication Engineers (IETE); Academic Excellence Award (1998) from Indian Government for his pioneering contributions to phase control modules for Rajendra Radar, Shri Om Prakash Bhasin Award (2009) in the field of Electronics and Information Technology, VASVIK Award (2012) for the contributions made to the area of Information, Communication Technology (ICT) and M N Saha Memorial Award (2013) from IETE.His name has recently figured in the Scopus Elsevier top 2% Scientists under the Category “Year 2021”. Additionally, Prof Koul has been bestowed the distinguished IETE-Lifetime Achievement Award 2023 by the IETE.
Arun Kumar
Arun Kumar is with the Centre for Applied Research in Electronics, Indian Institute of Technology, Delhi since 1997. He became professor in 2008 and has served as head of Centre for more than 7 years. He obtained the BTech, MTech and PhD degrees from Indian Institute of Technology Kanpur in 1988, 1990 and 1995, respectively. He was visiting researcher at the University of California, Santa Barbara, USA from 1994 to 1996 before joining IIT Delhi. His research interests are in digital signal processing, underwater and air acoustics, human and machine speech communication, and multi-sensor data fusion.
Professor Arun Kumar is an inventor on 10 granted US patents. He has guided 16 PhD theses and 180 master’s theses. He has authored/co-authored 160 papers in peer reviewed journals and conferences. He has been project investigator/co-investigator for 72 funded R&D projects from industry and government. These projects have led to several technology and know-how transfers. Many of the technologies co-developed by him are deployed in the field and are in practical use. Professor Arun Kumar has served on several technical and organization committees of conferences, and on national level committees in electronics and defence fields. He is co-founder and director of a company that develop signal processing and AI based technologies and products for speech-based and multi-modal human and machine. He is currently deputy editor-in-chief of IETE Journal of Research. Email: [email protected]
Ranjan K Mallik
Ranjan K Mallik (FIETE, FIEEE, FIET, FTWAS, FNAE, FNA, FNASc, FASc) is an Institute chair professor in the Department of Electrical Engineering, Indian Institute of Technology (IIT) Delhi. He received the BTech degree from IIT Kanpur and the MS and PhD degrees from the University of Southern California, Los Angeles, all in electrical engineering. He has worked as a scientist in the Defence Electronics Research Laboratory, Hyderabad, India, and as a faculty member in IIT Kharagpur and IIT Guwahati. His research interests are in diversity combining and channel modelling for wireless communications, space-time systems, cooperative communications, multiple access systems, power line communications, molecular communications, difference equations, and linear algebra. He is a recipient of the Shanti SwarupBhatnagar Prize, the Hari Om Ashram Prerit Dr Vikram Sarabhai Research Award, the Khosla National Award, the IETE Ram LalWadhwa Award, the IEI-IEEE Award for Engineering Excellence, and the JC Bose Fellowship. He is a Member of Eta Kappa Nu, and a Fellow of IEEE, the Indian National Academies INAE, INSA, NASI, and IASc, TWAS, the West Bengal Academy of Science and Technology, IET (UK), IETE (India), The Institution of Engineers (India), and the Asia-Pacific Artificial Intelligence Association. He served as an area editor and an editor for the IEEE Transactions on Wireless Communications, and as an editor for the IEEE Transactions on Communications. He was a Technical Program Committee (TPC) co-chair for the Wireless Communications Symposium of IEEE GLOBECOM 2008 and IEEE ICC 2010, a TPC co-chair for the PHY Track of IEEE WCNC 2013, and a TPC co-chair for the Communication Theory Symposium of IEEE ICC 2021. He is currently deputy editor-in-chief of IETE Journal of Research. Email: [email protected]